<?xml version='1.0' encoding='UTF-8'?><metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns="http://dublincore.org/documents/dcmi-terms/"><dcterms:title>Code of "Expected Effects of a Global Transformation of Agricultural Pest Management"</dcterms:title><dcterms:identifier>https://doi.org/10.60507/FK2/FE09XJ</dcterms:identifier><dcterms:creator>Möhring, Niklas</dcterms:creator><dcterms:creator>Ba, Malick</dcterms:creator><dcterms:creator>Braga, Anna</dcterms:creator><dcterms:creator>Gaba, Sabrina</dcterms:creator><dcterms:creator>Gagic, Vesna</dcterms:creator><dcterms:creator>Kudsk, Per</dcterms:creator><dcterms:creator>Larsen, Ashley</dcterms:creator><dcterms:creator>Mesnage, Robin</dcterms:creator><dcterms:creator>Niggli, Urs</dcterms:creator><dcterms:creator>Qaim, Matin</dcterms:creator><dcterms:creator>Schreinemachers, Pepijn</dcterms:creator><dcterms:creator>Stamm, Christian</dcterms:creator><dcterms:creator>de Vries, Wim</dcterms:creator><dcterms:creator>Finger, Robert</dcterms:creator><dcterms:publisher>bonndata</dcterms:publisher><dcterms:issued>2025-10-29</dcterms:issued><dcterms:modified>2025-12-09T14:01:10Z</dcterms:modified><dcterms:description>The here presented dataset provides code to replicate the analysis of Möhring et al. (2025) on expected effects of a global transformation of agricultural pest management based on an online survey conducted in 2022 with 517 senior scientific experts from key agricultural regions and disciplines. The assessment framework covers 24 indicators in the economic, human health, food security, social, and environmental domains. It is anonymized. It further contains information on respondent characteristics and co-variates for the socio-economic and environmental state of the assessed regions from literature. The data was collected in 2022 with an online survey in Limesurvey. The data was collected to assess expected effects of a global transformation to pest management with zero or minimal pesticide use. This is a pressing challenge in global agriculture and relates to national and global policy targets on pesticide reduction. 

The code in R can be used to replicate results of the analysis.</dcterms:description><dcterms:subject>Agricultural Sciences</dcterms:subject><dcterms:subject>Earth and Environmental Sciences</dcterms:subject><dcterms:subject>Social Sciences</dcterms:subject><dcterms:language>English</dcterms:language><dcterms:IsSupplementTo>Möhring, N., Ba, M. N., Braga, A., Gaba, S., Gagic, V., Kudsk, P., Larsen, A., Mesnage, R., Niggli, U., Qaim, M., Schreinemachers, P., Stamm, C., de Vries, W., Finger, R. (2025). Expected Effects of a Global Transformation of Agricultural Pest Management. Nature Communications, 16, 10901 (2025). https://doi.org/10.1038/s41467-025-66982-4.</dcterms:IsSupplementTo><dcterms:date>2025-10-29</dcterms:date><dcterms:contributor>Möhring, Niklas</dcterms:contributor><dcterms:dateSubmitted>2025-10-26</dcterms:dateSubmitted><dcterms:temporal>2022-03-20</dcterms:temporal><dcterms:temporal>2022-10-20</dcterms:temporal><dcterms:relation>Möhring, Niklas; Ba, Malick; Braga, Anna; Gaba, Sabrina; Gagic, Vesna; Kudsk, Per; Larsen, Ashley; Mesnage, Robin; Niggli, Urs; Qaim, Matin; Schreinemachers, Pepijn; Stamm, Christian; de Vries, Wim; Finger, Robert, 2025, "Dataset for „Expected Effects of a Global Transformation of Agricultural Pest Management“", https://doi.org/10.60507/FK2/XWSS9W, bonndata</dcterms:relation><dcterms:type>Quantitative</dcterms:type><dcterms:type>Survey data</dcterms:type><dcterms:source>Möhring, N., Ba, M. N., Braga, A., Gaba, S., Gagic, V., Kudsk, P., Larsen, A., Mesnage, R., Niggli, U., Qaim, M., Schreinemachers, P., Stamm, C., de Vries, W., Finger, R. (2025). Expected Effects of a Global Transformation of Agricultural Pest Management. Nature Communications (In Press).

International Food Policy Research Institute (IFPRI), 2024, "Global Spatially-Disaggregated Crop Production Statistics Data for 2020 Version 1.0.0", https://doi.org/10.7910/DVN/SWPENT, Harvard Dataverse, V1.</dcterms:source><dcterms:license>CC BY 4.0</dcterms:license></metadata>